It’s that time of year when we need to start thinking about what R Conferences we would like to (and can!) attend. To help plan your (ahem) work trips, we thought it would be useful to list the upcoming main attractions. We maintain a list of upcoming rstats conferences. To keep up to date, just

Can’t be bothered reading, tell me now Getting started Setting up R Opening ports ready for RStudio Installing RStudio Nicer URLs Adding SSL Can’t be bothered reading, tell me now Host RStudio server on an azure instance. Configure the instance to access RStudio with a nice url Getting started Azure is cloud computing framework provided

The prize How do I enter? FAQ Today we are happy to announce our Stan contest. Something we feel very strongly at Jumping Rivers is giving back to the community. We have benefited immensely from hard work by numerous people, so when possible, we try to give something back. This year we’re sponsoring StanCon 2018.

Prerequisites Analysis Summary The plotly package. A godsend for interactive documents, dashboard and presentations. For such documents, there is no doubt that anyone would prefer a plot created in plotly rather than ggplot2. Why? Using plotly gives you neat and crucially interactive options at the top, whereas ggplot2 objects are static. In an app we

Nested timings 1) Sys.time() 2) The tictoc package Comparing functions 1) system.time() 2) The microbenchmark package Conclusion As time goes on, your R scripts are probably getting longer and more complicated, right? Timing parts of your script could save you precious time when re-running code over and over again. Today I’m going to go through

Stan is freedom-respecting, open-source software for facilitating statistical inference at the frontiers of applied statistics. Or to put it another way, it makes Bayesian inference fast and (a bit) easier. StanCon is the premier conference for all things Stan related and this year it will take place at the Asilomar Conference Grounds, a National Historic

Can’t be bothered reading, tell me now The wonder of CRAN Parallel package installation: Ncpus Does it work? A permanent change: .Rprofile References Can’t be bothered reading, tell me now A simple one line tweak can significantly speed up package installation and updates. The wonder of CRAN One of the best features of R is